Presently, numerous options exist for chemicals and materials detection involving laboratory and field-based monitoring, verification and accounting (MVA) sensors and techniques that can quantify emissions. MVA techniques include atmospheric monitoring technologies, remote sensing and near-surface monitoring technologies, and intelligent monitoring concepts. Specific technological approaches include: atmospheric point samplers (“sniffers” based upon a wide-range of techniques such as electrochemical (membrane), infrared, semiconductor, and ionization/ion mobility); eddy covariance (a.k.a., eddy correlation and eddy flux, including fiber optic sensor arrays based upon photonic bandgap (PBG)); gas chromatography (GC) and accelerator mass spectroscopy (AMS) techniques (including thermal desorption, chemoluminescence, time-of-flight mass spectrometry techniques); acoustic wave and ultrasonic detection; photoacoustic spectroscopy; laser fluorosensor (LFS) (fluorescence energy measurement); various Raman scattering techniques; gamma-ray spectroscopy; laser holographic sensing; various satellite and airborne sensors; and spectroscopic techniques such as back-scatter Light Detection and Ranging (LIDAR), laser-based Differential Absorption LIDAR (DIAL), and Differential Optical Absorption Spectroscopy (DOAS).
However, despite the large number of possible detection technologies, a number of challenges remain to be addressed: (1) the environmental background flux which continues to adversely affect detection sensitivity; (2) turning measurements into an appropriate area-integrated, mass balance (quantity) is difficult; (3) small “patch” area samples which are not ideally suited for cost-effectively and comprehensively observing a large area; and (4) the statistical “spatial resolution” of present monitoring systems is too coarse and, thus they are unable to easily (e.g., rapidly) locate and characterize an individual hazard (e.g., threat) within the larger landscape (e.g., separate one contaminated vehicle out of many uncontaminated vehicles).
With specific regard to detection sensitivity and operating in the real world, many anthropogenic emissions are present that negatively affect relevant measurements systems. For example: normal vehicle emissions such as ammonia (NH3); carbon black from tires and combusted diesel; production of electricity; cement, chemical/fertilizer, mining and ethanol emissions; pollen and attractants from certain flowering plants; volatile organic compounds (VOCs); farming and ranching practices such as pesticide and herbicide application; and fine particulate matter in the air. Furthermore, natural skin oils (e.g., squalene), chemicals used in processed food (e.g., binders and preservatives), certain soaps/shampoos, deodorants/antiperspirants, perfumes/colognes, and insect repellents are all known to confuse or unfavorably affect the sensitivity of many detection techniques. In these environments and situations not only is the detection of a specific gaseous, vapor/aerosol, solid or liquid species complicated by the background and contaminates present, but these naturally occurring and anthropogenic sources of interferents will spoof many present detection techniques with false readings concerning an actual hazard.
Thus, there are few analytic tools available that can be used to quantify and characterize, non-intrusively (not slowing or down-grading the testing tempo, along with supporting moving object testing modalities) and in situ at the low concentrations typically required (in the low parts-per-billion to low parts-per-trillion range). While many techniques from material sciences are pertinent, each one has shortcomings that prevent its widespread adoption in a real-time production setting. More importantly, many measurement techniques, which might be considered for use, are unable to adequately distinguish chemicals of interest from interferents; such interferents often being the result of human-caused situations, or naturally occurring sources. Furthermore, there may be practical confusion of the significance of a detection event due to many chemicals' dual-use applications. Even under well controlled conditions, background sources may dominate over the target materials of interest. Viable solutions are further complicated when the desire is a single detection technology that needs to detect a wide-range of chemicals with significantly different molecular structures, in multiple phases (solid, liquid and/or gas) of matter, instead of just a few closely related species in a single phase of matter. Therefore, a way to easily and affordably distinguish different sources would be of practical value to chemical and materials detection. In contrast to the prior art, the DES technique of the present invention offers agility in the range of detectable species, in all phases (solid, liquid and gas) of matter, and has a unique tolerance to interferents.